Artificial Intelligence for Sexual, Reproductive and Maternal Health: A Scoping Review (Preprint) DOI

Martín Sabán,

Melina Denise Zavala, Adolfo Rubinstein

et al.

Published: Aug. 1, 2024

BACKGROUND - OBJECTIVE To survey and analyze the applications of artificial intelligence tools in field sexual, reproductive maternal health Latin America Caribbean. METHODS A scoping review was conducted using methodological framework proposed by Arksey O'Malley PRISMA statement for Systematic Reviews Meta-analyses, extension Scoping Reviews. The search carried out PubMed, Scielo, Cochrane Lilacs. RESULTS Of 1,518 articles identified, 143 were included analyzed. evidences predominant focus prenatal, childbirth, postnatal care, as well prevention, detection, treatment cancers organs. mainly use machine learning deep techniques, are different stages development: 48% represent exploratory projects, 17% operational but do not have a results report, 35% projects implemented real contexts provide evidence effectiveness used. CONCLUSIONS need to diversify essential services ensure inclusion diverse populations equitable effective access them is highlighted CLINICALTRIAL

Language: Английский

Violence against women and girls research: Leveraging gains across disciplines DOI Creative Commons
Kathryn Falb, Amber Peterman, Ragnhild Nordås

et al.

Proceedings of the National Academy of Sciences, Journal Year: 2025, Volume and Issue: 122(4)

Published: Jan. 23, 2025

Violence against women and girls (VAWG) is a leading cause of mortality morbidity worldwide, linked to numerous health, economic, human rights outcomes. Target 5.2 the Sustainable Development Goals calls for elimination all forms VAWG; however, progress toward achieving this goal has been inadequate. A lack sufficient data evidence hindered global efforts meet target hold governments accountable action. While there have substantial advancements in VAWG research methodology over past three decades, researchers from diverse disciplines tend work silos, inhibiting research. To address challenge, we offer four key recommendations support expanding transdisciplinary approaches: 1) leverage insights variety sources, 2) improve precision definitions outcomes, 3) create strategies underreporting, 4) advance ethics equity. We conclude with call action researchers, institutions, donors foster collaboration, learning, cross-fertilization across scientific fields accelerate prevention now future generations.

Language: Английский

Citations

0
Artificial Intelligence for Sexual, Reproductive and Maternal Health: A Scoping Review (Preprint) DOI

Martín Sabán,

Melina Denise Zavala, Adolfo Rubinstein

et al.

Published: Aug. 1, 2024

BACKGROUND - OBJECTIVE To survey and analyze the applications of artificial intelligence tools in field sexual, reproductive maternal health Latin America Caribbean. METHODS A scoping review was conducted using methodological framework proposed by Arksey O'Malley PRISMA statement for Systematic Reviews Meta-analyses, extension Scoping Reviews. The search carried out PubMed, Scielo, Cochrane Lilacs. RESULTS Of 1,518 articles identified, 143 were included analyzed. evidences predominant focus prenatal, childbirth, postnatal care, as well prevention, detection, treatment cancers organs. mainly use machine learning deep techniques, are different stages development: 48% represent exploratory projects, 17% operational but do not have a results report, 35% projects implemented real contexts provide evidence effectiveness used. CONCLUSIONS need to diversify essential services ensure inclusion diverse populations equitable effective access them is highlighted CLINICALTRIAL

Language: Английский

Citations

0